ABSTRACT Despite the over 90% efficacy of diabetic retinopathy (DR) treatment, it continues to be the leading cause of blindness in working age Americans. Over 30 million adults in the US have diabetes. Of these, 28% will develop DR and 4.4% will develop vision-threatening DR (VTDR). Currently, less than half of all patients with diabetes receive the recommended annual dilated eye exam and, of those diagnosed with VTDR, only 30% undergo timely treatment. New screening protocols are increasing screening effectiveness, however, even if every patient is screened, the majority of those at increased risk do not receive evidence-based follow-up care; a classic public health failure common to population-based screening. With expertise in health systems engineering and ophthalmology, the research team is uniquely suited to eliminate the root causes of this failure; resulting in a new, comprehensive care model designed to prevent blindness for the 8.9 million Americans with DR. Retinal Care Inc. (RCI)?s focus is on eliminating blindness by applying targeted care coordination for patients at increased risk for VTDR; ensuring they progress through the care path to treatment. However, two significant deficiencies weaken RCI?s ability to deliver effective care coordination. The first is insufficient capacity due to coordinating care for 35% of all patients, though less than 5% actually have VTDR. This derives from the low positive predictive value of the current system, based on a handheld electroretinography and pupillography device deployed in a primary care setting. The first aim is to improve the ability to classify a patient as low- risk for VTDR, thereby reducing the care coordination burden and improving quality and effectiveness. Aim 1: Improve the ability to accurately identify patients at increased risk for VTDR by including patient health and demographic attributes in a machine learning based predictive algorithm for VTDR diagnosis. Patient clusters will be identified (a) and used to create sub-population specific risk models (b). The second deficiency is the lack of adherence to follow-up and treatment after identification as increased risk for VTDR. Once a patient is identified as increased risk, the care coordination of the RCI DR program has averaged over five phone calls per patient to achieve follow-up with an eye care provider. The second aim is to identify and eliminate these barriers to coordinated care between patient and provider. Aim 2 Apply text analytics and simulation to improve access, compliance, cost, and equity by enhancing care coordination, from diagnosis to treatment, for patients at increased risk for VTDR. The application of data analytics and systems engineering methods to integrate and improve each critical component of the care path, access to care, accuracy of diagnosis, and adherence to follow-up and treatment, will enable a paradigm shift in DR treatment. RCI?s platform is designed to eliminate deficiencies of the current care delivery model by delivering a first-of-its-kind, end-to-end solution for diabetic retinopathy care.